Triple

T2494461
Position Surface form Disambiguated ID Type / Status
Subject ORCA card E52122 entity
Predicate hasVariant P455 FINISHED
Object adult ORCA card E52122 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: adult ORCA card | Statement: [ORCA card, hasVariant, adult ORCA card]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: adult ORCA card
Context triple: [ORCA card, hasVariant, adult ORCA card]
  • A. ORCA card chosen
    The ORCA card is a reusable, contactless smart card used to pay fares across multiple public transit systems in the Puget Sound region of Washington State.
  • B. Opal card
    The Opal card is a reusable, contactless smartcard used to pay for public transport across much of New South Wales, Australia.
  • C. Breeze Card
    The Breeze Card is a reusable smart fare card used for paying transit fares across the Metropolitan Atlanta Rapid Transit Authority (MARTA) system in Atlanta, Georgia.
  • D. Clipper card
    The Clipper card is a reloadable contactless smart card used to pay fares across multiple public transit systems in the San Francisco Bay Area.
  • E. TransLink card
    The TransLink card was a contactless smart card used for fare payment on public transit systems in the San Francisco Bay Area before being succeeded by the Clipper card.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69ab4955111c8190835bf619adec21ff completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abd193fe7881909b08768c44b15049 completed March 7, 2026, 7:19 a.m.
NED1 Entity disambiguation (via context triple) batch_69af1f9608e48190825417943e8c4559 completed March 9, 2026, 7:29 p.m.
Created at: March 6, 2026, 9:45 p.m.